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SCImago
Q2
WOS
Q3
Impact factor
2.2
SJR
0.876
CiteScore
6.9
Categories
Computer Networks and Communications
Software
Areas
Computer Science
Years of issue
1995-2023
journal names
Computer Communication Review
ACM SIGCOMM Computer Communication Review
ACM SIGCOMM COMP COM
Top-3 citing journals

Lecture Notes in Computer Science
(5761 citations)

Computer Networks
(3412 citations)

IEEE/ACM Transactions on Networking
(3412 citations)
Top-3 organizations

University of California, Berkeley
(118 publications)

Stanford University
(98 publications)

University of California, San Diego
(93 publications)

Princeton University
(8 publications)

Columbia University
(7 publications)

University of Twente
(6 publications)
Top-3 countries
Most cited in 5 years
Found
Publications found: 7569
Q2

Mass Spectrometry–Based Proteomics in Clinical Diagnosis of Amyloidosis and Multiple Myeloma: A Review (2012–2024)
Kratka K., Sistik P., Olivkova I., Kusnierova P., Svagera Z., Stejskal D.
ABSTRACTProteomics is nowadays increasingly becoming part of the routine clinical practice of diagnostic laboratories, especially due to the advent of advanced mass spectrometry techniques. This review focuses on the application of proteomic analysis in the identification of pathological conditions in a hospital setting, with a particular focus on the analysis of protein biomarkers. In particular, the main purpose of the review is to highlight the challenges associated with the identification of specific disease‐causing proteins, given their complex nature and the variety of posttranslational modifications (PTMs) they can undergo. PTMs, such as phosphorylation and glycosylation, play critical roles in protein function but can also lead to diseases if dysregulated. Proteomics plays an important role especially in various medical fields ranging from cardiology, internal medicine to hemato‐oncology emphasizing the interdisciplinary nature of this field. Traditional methods such as electrophoretic or immunochemical methods have been mainstay in protein detection; however, these techniques are limited in terms of specificity and sensitivity. Examples include the diagnosis of multiple myeloma and the detection of its specific protein or amyloidosis, which relies heavily on these conventional methods, which sometimes lead to false positives or inadequate disease monitoring. Mass spectrometry in this respect emerges as a superior alternative, providing high sensitivity and specificity in the detection and quantification of specific protein sequences. This technique is particularly beneficial for monitoring minimal residual disease (MRD) in the diagnosis of multiple myeloma where traditional methods fall short. Furthermore mass spectrometry can provide precise typing of amyloid proteins, which is crucial for the appropriate treatment of amyloidosis. This review summarizes the opportunities for proteomic determination using mass spectrometry between 2012 and 2024, highlighting the transformative potential of mass spectrometry in clinical proteomics and encouraging its wider use in diagnostic laboratories.
Q2

Comparison of Mid‐Infrared and Ultraviolet Lasers Coupled to the MALDESI Source for the Detection of Secondary Metabolites and Structural Lipids in Arabidopsis thaliana
Ashbacher S., Manni J., Muddiman D.
ABSTRACTMatrix‐assisted laser desorption electrospray ionization (MALDESI) conventionally utilizes a mid‐infrared (IR) laser for the desorption of neutrals, allowing for detection of hundreds to thousands of analytes simultaneously. This platform enables mass spectrometry imaging (MSI) capabilities to not only detect specific molecules but also reveal the distribution and localization of a wide range of biomolecules across an organism. However, an IR laser comes with its disadvantages when imaging plants. At a mid‐IR wavelength (2970 nm), the compartmentalized endogenous water within the leaf structure acts as an internal matrix, causing rapid heating, and, in turn, degrades the spatial resolution and signal quality. An ultraviolet (UV) laser operates at wavelengths that overlap with the absorption bands of secondary metabolites allowing them to serve as sacrificial matrix molecules. With the integration and optimization of a 355 nm UV laser into the MALDESI‐MSI NextGen source for the analysis of plants, we were able to detect diverse molecular classes including flavonoids, fatty acid derivatives, galactolipids, and glucosinolates, at higher ion abundances when compared to the mid‐IR laser. These results show that re‐visiting UV‐MALDESI‐MSI, without the need for an exogenous matrix, provides a promising approach for the detection and imaging of important analytes in plants.
Q2

Minimizing Variable Downhole Fractionation in U–Pb Zircon Geochronology by LA‐MC‐ICP‐MS at Smaller Spot Size
Singhal S., Singh S., Singh D.
ABSTRACTThe development of LA‐ICPMS and LA‐MC‐ICPMS resulted in analytical methods for zircon geochronology using a 20‐ to 60‐μm laser spot size. A high amount of complexly zoned zircons promotes the requirement of U–Pb dating at smaller spot sizes. When spot size reduces, downhole fractionation (DHF) increases, increasing the DHF discrepancy between zircon grains and the primary reference zircon standard and resulting in inaccurate results. With MC‐ICPMS's high sensitivity and multi‐collector capabilities, this work attempts to accurately determine age with spatial resolutions below 20 μm. Three well‐characterized zircon standards (91500, GJ‐1, and Plešovice) were tested at spot sizes of 35, 20, 15, and 10 μm. Laser and mass spectrometry tuning, laser shot count, and ablation time have been optimized to reduce the DHF effect on measurement accuracy. Static ablation of 35‐ to 15‐μm spots with 150 laser shot counts (30 s) yielded precision of less than 1.5% and age offset of less than 2%. The DHF differs significantly from the reference standard and two test zircon samples used for validation, with an age offset of 4% at 10‐μm spot sizes. Masking shot counts from the end enhanced accuracy, notably for lower laser shot counts and shorter ablation times. At 75 laser shot counts, precision reached 1.4% and age offsets reduced to 1.6% for 206Pb/238U age. This method minimizes laser shot counts to avoid sampling two age groups. Higher zircon DHF variability at smaller spot sizes may influence a well‐calibrated, sensitive LA‐MC‐ICP‐MS analytical figure of merit.
Q2

CID‐Induced Formation of Deprotonated Cyclic Peptide Ions From Anionic Adducts
Modzel M., Stefanowicz P.
ABSTRACTMS analysis of cyclic peptides in negative ion mode has been a challenge, in particular if the peptide does not contain acidic functional groups. In this paper, we present a way to easily produce negative ions from anionic peptide adducts, utilising collision‐induced dissociation (CID)‐mediated elimination. Using two different mass spectrometers, we have generated series of adducts of three cyclic and one linear peptide with various anions. They were then isolated and subjected to CID with a range of collision energies. The deprotonation percentage was then calculated from the resultant spectrum, and compared between the spectrometers, as well as with an external reference—proton affinity values. The susceptibility to deprotonate by detaching a HX moiety is proportional to the proton affinity of the X− species. Also, the linear peptide deprotonated more readily than the cyclic ones. On the other hand, lack of amino or acidic groups resulted in higher collision voltage (CV) necessary for the formation of deprotonated species. Moreover, the exact propensity for neutral loss depends on the ion temperature, which differs between mass spectrometers. We have developed a facile method for generating peptide anions for MS analysis of cyclic peptides, which works even if the peptide in question does not have easily ionisable groups. The deprotonated species generated in this way can be fragmented again in order to identify the peptide.
Q2

Mechanistic Insights Into the Dissociative Photoionization Pathways of Ethyl Propionate: A Combined Experimental and Theoretical Approach
Wang H., Shan X., Liu F., Wang Z., Sheng L., Sui R.
ABSTRACTEthyl propionate (C5H10O2, EP) has been extensively studied in the fields of biofuels and atmospheric chemistry. However, its vacuum ultraviolet (VUV) photoionization has not been investigated. This study examines the photoionization process of EP using tunable VUV synchrotron radiation, coupled with a reflectron time‐of‐flight mass spectrometer. This method yielded the photoionization mass spectrum of EP and photoionization efficiency (PIE) spectra of 10 identified fragment ions (i.e., C4H7O2+., C3H7O2+., C3H6O2+., C3H5O2+., C3H6O+., C3H5O+., C3H4O+., C2H5O+., C2H5+., and C2H4+.). The results, interpreted with the aid of high‐accuracy theoretical calculations, conclude possible formation mechanisms for each fragment ion. In the dissociation pathway of EP's cation, intramolecular hydrogen shifts and bond cleavage are the predominant processes. The C3H7O2+. and C2H4+. reaction channels do not arise from one‐step bond cleavage, but their reaction energy barriers are influenced by product energy, making them comparable to direct reaction channels. The active reaction sites within the molecules are elucidated using Laplacian bond order (LBO). Rate constants are calculated using RRKM theory, which confirms the kinetic factors governing the EP reaction process. This study provides a detailed understanding of the photoionization and dissociation of the main ions of EP within the 9.35–15.50 eV photon energy range.
Q2

Zn(II) Affinity and Structural Conformations of 2His‐2Cys Zinc Finger‐Like Motif Peptide Determined by Ion Mobility–Mass Spectrometry and PM6 Molecular Modeling
Adomako R., Owusu M., Oberdick R., Senyah K., Asare P., Spezia R., Angel L.
ABSTRACTThis study focuses on investigating the conformational structure and zinc(II) affinity of a zinc finger‐like motif (ZFM) peptide with the sequence acetyl‐His1‐Cys2‐Gly3‐Pro4‐Gly5‐His6‐Cys7, where bold highlights the potential zinc(II) binding sites. Zinc fingers are crucial protein motifs known for their high specificity and affinity for zinc ions. The ZFM peptide's sequence contains the 2His‐2Cys zinc‐binding sites similar to those in natural zinc finger proteins but without the hydrophobic core, making it a valuable model for studying zinc(II)–peptide interactions. Previous research on related peptides showed that collision cross sections and B3LYP modeling predicted that the His‐2Cys‐carboxyl terminus coordination of zinc(II) was more stable than the 2His‐2Cys. Employing a comprehensive approach integrating ion mobility–mass spectrometry and theoretical modeling techniques, various zinc(II) binding modes of the ZFM have been thoroughly compared to ascertain their influence on the competitive threshold collision‐induced dissociation method for measuring the relative gas‐phase Zn(II) affinity of the ZFM peptide. The measured Zn(II) affinity of ZFM is greater than those measured recently for two peptides with similar primary structures, acetyl‐His1‐Cys2‐Gly3‐Pro4‐Gly5‐Gly6‐Cys7 and acetyl‐Asp1‐His2‐Gly3‐Pro4‐Gly5‐Gly6‐Cys7, indicating the preference for the His1‐Cys2‐His6‐Cys7 side groups for coordinating zinc(II) over the His‐2Cys‐carboxyl terminus or Asp‐His‐Cys‐carboxyl terminus in these related heptapeptides.
Q2

Erratum—Integrating DFT and CI‐MS Techniques to Assess Benzophenone Derivatives in Food Packaging: Implications for Enhancing Food Quality and Safety
Bhatia M.
Q2
Journal of Mass Spectrometry
,
2025
,
citations by CoLab: 0

Q2

digitalMALDI: A Single‐Particle–Based Mass Spectrometric Detection System for Biomolecules
Chen D., Bryden W., McLoughlin M., Ecelberger S., Cornish T., Moore L., Regan K.
ABSTRACTThe development of a real‐time system for characterizing individual biomolecule‐containing aerosol particles presents a transformative opportunity to monitor respiratory conditions, including infections and lung diseases. Existing molecular assay technologies, although effective, rely on costly reagents, are relatively slow, and face challenges in multiplexing, limiting their use for real‐time applications. To overcome these challenges, we developed digitalMALDI, a laser‐based mass spectrometry system designed for single‐particle characterization. digitalMALDI operates as a near real‐time platform that directly samples aerosols, bypassing the need for complex and time‐consuming sample preparation. To demonstrate the feasibility of this approach, intact insulin protein was used as a representative target. Results showed that digitalMALDI is capable of detecting 1 pg of insulin protein in single aerosol particles, suggesting that the system has a broad application for disease diagnosis, environmental monitoring, and biosecurity management.
Q2

Feasibility of IR‐MALDESI Mass Spectrometry Imaging of PFAS
Martin A., Joignant A., Farrell M., Planchart A., Muddiman D.
ABSTRACTPerfluoroalkyl and polyfluoroalkyl substances (PFAS) are a class of emerging contaminants that have been in use industrially since the 1940s. Their long‐term and extensive commercial use has led to their ubiquitous presence in the environment. The ability to measure the bioconcentration and distribution of PFAS in the tissue of aquatic organisms helps elucidate the persistence of PFAS as well as environmental impacts. Traditional analysis by LC–MS/MS can measure total PFAS concentrations within an organism but cannot provide comprehensive spatial information regarding PFAS concentrations within the organism. In the current study, we used infrared matrix‐assisted laser desorption electrospray ionization (IR‐MALDESI) to determine the limit of detection (LOD) of several PFAS utilizing a commercial standard mix spotted on mouse liver tissue. The traditional ice matrix and an alternative matrix, 1,8‐bis (tetramethylguanidino)naphthalene (TMGN), were explored when determining the limits of detection for various PFAS by IR‐MALDESI. The ice matrix alone resulted in a higher response than the combination of TMGN and ice. The resulting LOD for perfluorooctane sulfonic acid (PFOS) on a per voxel basis was 0.16 fmol/voxel. For comparison, zebrafish that were exposed to perfluorooctanoic acid (PFOA), PFOS, and perfluorohexanesulfonic acid (PFHxS) at different concentrations were homogenized, and PFAS were extracted by solid–liquid extraction, purified by solid phase extraction, and analyzed by LC–MS/MS to determine the level of bioaccumulation in the zebrafish. PFOS resulted in the highest level of bioaccumulation (731.9 μg/kg, or 234.2 fg/voxel). A zebrafish that had been exposed to a PFAS mixture of PFOA (250 ng/L), PFOS (250 ng/L), and PFHxS (125 ng/L) was cryosectioned and analyzed by IR‐MALDESI. Images could not be generated as the accumulation of PFAS in the sectioned tissue was below detection limit of the technique.
Q2

Sodiation of Enhanced Green Fluorescent Protein (EGFP) in Basic Solution Studied by Electrospray Mass Spectrometry
Hiraoka K., Ninomiya S., Rankin‐Turner S., Suzuki N., Akashi S.
ABSTRACTIn our previous work, the sodiation of melittin, cytochrome c, and ubiquitin in a 1 mM NaOH water/methanol solution was studied by electrospray mass spectrometry. It was suggested that the α‐helix is more resistant to sodiation than the β‐sheet. In this study, sodiation of enhanced green fluorescent protein (EGFP) composed of a β‐barrel was studied in 1% CH3COOH (AcOH) or 1 mM NaOH water/methanol solution by electrospray mass spectrometry. Although EGFP was denatured in an acidic solution, it maintains a near‐native structure in a basic solution. For the 1% AcOH solution, the protonated EGFP, [EGFP + nH − mH + mNa]n+, with n = 14 − 36 and m = 0 was detected. For 1 mM NaOH, the number n for [EGFP + nH − mH + mNa]n+ was found to increase with the sodiation number m and vice versa for [EGFP + nH − mH + mNa]n−. Namely, Na+ adducts counteract the negative charges of deprotonated acidic residues. The protonated EGFP detected as major ions for basic 1 mM NaOH was ascribed to the more surface‐active H3O+(aq) than OH−(aq).
Q2

Application of Online Multi‐Internal Standard Calibration for Determination of Iodine by ICP‐MS
Zhou L., Lin X., Suo L., Ma L., Hu G., Xia X., Li M., Huang W., Jin Y.
ABSTRACTThis study presents a comprehensive evaluation of the application of online multi‐internal standard calibration (M.ISC) in determining iodine concentrations through inductively coupled plasma mass spectrometry (ICP‐MS). Notably, M.ISC streamlines the calibration process by requiring only a single standard solution, thereby enhancing sample throughput and minimizing liquid waste. In addition, unlike conventional internal standard (IS) methods, M.ISC omits the need for time‐consuming species identification by utilizing multiple IS species simultaneously to minimize signal biases. The effectiveness of M.ISC was validated through the analysis of six standard reference samples, with the results of LOD and LOQ also being calculated by the error propagation approach. The traditional chemical analytical methods (TCAM), external standard calibration (EC) and single IS methods were also evaluated as comparative purpose. Nonetheless, M.ISC emerges as a straightforward matrix‐correction strategy, offering a simple and efficient alternative to traditional calibration methods for iodine detection by ICP‐MS.
Q2

Cryogenic TOF‐SIMS Around Sublimation Temperature of Quench‐Condensed Noble Gas (Ne, Ar, and Kr) Films
Suzuki T.
ABSTRACTA possible TOF‐SIMS analysis of surface phase transitions has recently been proposed for limited cases such as polymers and ionic liquids. In the present study, we have extended this analysis to quench‐condensed noble gas films. The newly developed cryogenic TOF‐SIMS allowed both measurements of TOF‐SIMS below 4 K, and low‐energy ion scattering spectroscopy that is used to prepare a clean surface. It was found that the TOF‐SIMS intensity variation by increasing the temperature at a constant ramp rate (temperature‐programmed TOF‐SIMS) shows steep changes due to sublimation. Thus, the possibility of analyzing the surface phase transition at the local region defined by the incident ion beam of (cryogenic) TOF‐SIMS was demonstrated in the present study.
Q2

Performance Optimization of a Large Geometry High Resolution‐Secondary Ion Mass Spectrometer (HR‐SIMS) for High Precision Measurements of Oxygen Isotopic Composition (δ18O) and U–Pb Geochronology in Zircon
Khandelwal D., Kumar P., Kumar P. ., Singh A., Rawat M., Dawar A., Sharma R., Ojha S., Gargari S., Mukherjee P. ., Chopra S., Pandey A. .
ABSTRACTA large geometry high resolution secondary ion mass spectrometer (HR‐SIMS) has been established as a part of the National Geochronology Facility (NGF) at Inter‐University Accelerator Centre (IUAC), New Delhi. The performance of the instrument related to high spatial resolution, high mass resolving power (MRP), sensitivity of the instrument to measure low abundant isotopes, and sensitivity of the instrument for 206Pb signal under different conditions are optimized and presented in this paper. We report the precision of the order of ~ 0.2‰ for oxygen isotopes measurement in 91500 reference material zircon and measured δ18O value of 10.08‰ ± 0.18‰ (2SD), which is in agreement with the recommended values. For U–Pb age measurement in zircon, Plešovice and FCT reference materials are measured as unknown and their 206Pb/238U ages agree with the reported values within the uncertainties. A long‐term evaluation of 206Pb/238UO and 206Pb/238U isotopic measurement ratio is also presented.
Q2

Bothersome Back Exchange in MALDI Plume and Its Impact on Hydrogen/Deuterium Exchange Mass Spectrometry Analysis
Lou X., van Houtem M., Lafleur R. ., Schoenmakers S. ., van Dongen J. ., Palmans A. .
ABSTRACTOne critical issue in hydrogen/deuterium exchange mass spectrometry (HDX MS) analysis is the deleterious back exchange. Herein, we report that when matrix‐assisted laser desorption/ionization (MALDI) is used, the MALDI process itself can also cause significant back exchange. The back exchange occurred inside the reactive MALDI plume was investigated by depositing a fully deuterated sample prepared in D2O on top of a preloaded dried layer of matrix. A benzene‐1,3,5‐tricarboxamide (BTA) compound that can form supramolecular polymer in water and five peptides of angiotensin II (AT), pentaglycine (5G), pentaalanine (5A), cyclohexaglycine (C6G), and cyclohexaalanine (C6A) were selected as the testing compounds. Just like the situation in solution, the back exchange for the side chains and end groups is fast in the MALDI plume, while for the backbone amides, it is slow and dependent on the primary structure of the peptide. For the peptides tested, 5%–15% of D‐labels in the backbone amides can be lost during the MALDI process. This degree of back exchange, although not an unbearable problem for most HDX MS applications as 85%–95% of the informative labels would still survive, could seriously limit the use of MALDI in the HDX MS analysis of supramolecular assemblies. For these assemblies, the EX1‐like mechanism with two distinct distributions is common, and the back exchange could gravely distort or even merge the distinct isotopic distributions, which are the characteristic symbols of EX1.
Q2

Ghost Peaks of Aromatic Metabolites Induced by Corona Discharge Artifacts in LC‐ESI‐MS/MS
Hongo Y., Fukuyama D., Chen L., Sekimoto K., Watanabe H.
ABSTRACTLC‐ESI‐MS/MS is a preferred method for detecting and identifying metabolites, including those that are unpredictable from the genome, especially in basal metazoans like Cnidaria, which diverged earlier than bilaterians and whose metabolism is poorly understood. However, the unexpected appearance of a “ghost peak” for dopamine, which exhibited the same m/z value and MS/MS product ion spectrum during an analysis of Nematostella vectensis, a model cnidarian, complicated its accurate identification. Understanding the mechanism by which “ghost peaks” appear is crucial to accurately identify the monoamine repertoire in early animals so as to avoid misassignments. Verification experiments showed that in‐source oxidation of tyramine, which produced an intense signal, was responsible for this “ghost peak.” This artifact commonly occurs among aromatic compounds with high signal intensities and appears at the same m/z as their respective in vivo oxidized metabolites. In metabolomics, spectra contain diverse signals from complex biological mixtures, making it difficult to recognize artifact peaks. To prevent misassignments, despite +16 Da differences, adequate chromatographic separation of metabolites from their respective in vivo oxidation precursors is necessary. Whereas both electrolysis and gas‐phase corona discharge can cause in‐source oxidation in ESI, corona discharge proved to be the dominant factor. Additionally, the presence of multiple oxygen atom sources was suggested by the voltage‐dependent mass shift of +16 Da to +18 Da of the “ghost peak” when using 18O‐labeled water as a solvent. Accurate metabolite identification using LC‐ESI‐MS/MS requires accounting for in‐source products that can mimic in vivo products.
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IOP Publishing
373 citations, 0.28%
|
|
331 citations, 0.24%
|
|
Trans Tech Publications
326 citations, 0.24%
|
|
American Physical Society (APS)
293 citations, 0.22%
|
|
World Scientific
256 citations, 0.19%
|
|
Social Science Electronic Publishing
214 citations, 0.16%
|
|
Cambridge University Press
184 citations, 0.14%
|
|
Emerald
155 citations, 0.11%
|
|
IOS Press
139 citations, 0.1%
|
|
Oxford University Press
137 citations, 0.1%
|
|
Science in China Press
131 citations, 0.1%
|
|
China Science Publishing & Media
117 citations, 0.09%
|
|
Public Library of Science (PLoS)
114 citations, 0.08%
|
|
proceedings of the vldb endowment
111 citations, 0.08%
|
|
Springer Publishing Company
105 citations, 0.08%
|
|
Walter de Gruyter
99 citations, 0.07%
|
|
Beijing University of Posts and Telecommunications
93 citations, 0.07%
|
|
AIP Publishing
87 citations, 0.06%
|
|
Information Processing Society of Japan
69 citations, 0.05%
|
|
Tech Science Press
65 citations, 0.05%
|
|
Institute for Operations Research and the Management Sciences (INFORMS)
62 citations, 0.05%
|
|
SPIE-Intl Soc Optical Eng
60 citations, 0.04%
|
|
Scientific Research Publishing
59 citations, 0.04%
|
|
PeerJ
58 citations, 0.04%
|
|
Chinese Academy of Sciences
57 citations, 0.04%
|
|
Pleiades Publishing
55 citations, 0.04%
|
|
55 citations, 0.04%
|
|
Science Alert
54 citations, 0.04%
|
|
King Saud University
46 citations, 0.03%
|
|
EDP Sciences
45 citations, 0.03%
|
|
Society for Industrial and Applied Mathematics (SIAM)
42 citations, 0.03%
|
|
Institute of Mathematical Statistics
41 citations, 0.03%
|
|
Academy Publisher
41 citations, 0.03%
|
|
The Royal Society
40 citations, 0.03%
|
|
Frontiers Media S.A.
35 citations, 0.03%
|
|
The Pennsylvania State University Press
34 citations, 0.03%
|
|
Privacy Enhancing Technologies Symposium Advisory Board
34 citations, 0.03%
|
|
Proceedings of the National Academy of Sciences (PNAS)
32 citations, 0.02%
|
|
American Institute of Aeronautics and Astronautics (AIAA)
27 citations, 0.02%
|
|
Morgan & Claypool Publishers
26 citations, 0.02%
|
|
Engineering and Technology Publishing
25 citations, 0.02%
|
|
proceedings - international symposium on computers and communications
24 citations, 0.02%
|
|
Zhejiang University Press
23 citations, 0.02%
|
|
Wuhan University
23 citations, 0.02%
|
|
Korean Institute of Communications Information Sciences
22 citations, 0.02%
|
|
Institute of Electrical Engineers of Japan (IEE Japan)
22 citations, 0.02%
|
|
JMIR Publications
20 citations, 0.01%
|
|
IntechOpen
18 citations, 0.01%
|
|
MIT Press
17 citations, 0.01%
|
|
Instrument Society of America
17 citations, 0.01%
|
|
American Institute of Mathematical Sciences (AIMS)
16 citations, 0.01%
|
|
Bentham Science Publishers Ltd.
15 citations, 0.01%
|
|
Hans Publishers
15 citations, 0.01%
|
|
Tsinghua University Press
14 citations, 0.01%
|
|
13 citations, 0.01%
|
|
Acta Physica Sinica, Chinese Physical Society and Institute of Physics, Chinese Academy of Sciences
13 citations, 0.01%
|
|
International Academy Publishing (IAP)
13 citations, 0.01%
|
|
American Society of Civil Engineers (ASCE)
12 citations, 0.01%
|
|
Steklov Mathematical Institute
12 citations, 0.01%
|
|
American Association for the Advancement of Science (AAAS)
10 citations, 0.01%
|
|
Mary Ann Liebert
10 citations, 0.01%
|
|
ASME International
10 citations, 0.01%
|
|
IACSIT Press
10 citations, 0.01%
|
|
European Control Association
10 citations, 0.01%
|
|
Research Square Platform LLC
9 citations, 0.01%
|
|
Korea Information Processing Society (KIPS)
8 citations, 0.01%
|
|
World Scientific and Engineering Academy and Society (WSEAS)
8 citations, 0.01%
|
|
7 citations, 0.01%
|
|
Fuji Technology Press
7 citations, 0.01%
|
|
Cold Spring Harbor Laboratory
7 citations, 0.01%
|
|
SAE International
7 citations, 0.01%
|
|
electronic proceedings in theoretical computer science, eptcs
6 citations, 0%
|
|
Alexandria University
6 citations, 0%
|
|
SPIIRAS
6 citations, 0%
|
|
American Chemical Society (ACS)
5 citations, 0%
|
|
Universitat Politecnica de Valencia
5 citations, 0%
|
|
Copernicus
5 citations, 0%
|
|
OpenEdition
5 citations, 0%
|
|
Research Institute of Signal Processing, Japan
5 citations, 0%
|
|
ASTES Journal
5 citations, 0%
|
|
University of Suceava
4 citations, 0%
|
|
4 citations, 0%
|
|
Operations Research Society of Japan
4 citations, 0%
|
|
4 citations, 0%
|
|
Eizo Joho Media Gakkai
4 citations, 0%
|
|
Inderscience Publishers
4 citations, 0%
|
|
Indian Society for Education and Environment
4 citations, 0%
|
|
Show all (70 more) | |
10000
20000
30000
40000
50000
60000
|
Publishing organizations
20
40
60
80
100
120
|
|
University of California, Berkeley
118 publications, 3.88%
|
|
Stanford University
98 publications, 3.22%
|
|
University of California, San Diego
93 publications, 3.06%
|
|
University of Cambridge
72 publications, 2.37%
|
|
Princeton University
70 publications, 2.3%
|
|
Georgia Institute of technology
65 publications, 2.14%
|
|
University of Washington
62 publications, 2.04%
|
|
Massachusetts Institute of Technology
59 publications, 1.94%
|
|
Carnegie Mellon University
55 publications, 1.81%
|
|
University of Wisconsin–Madison
50 publications, 1.64%
|
|
University of Southern California
49 publications, 1.61%
|
|
University of California, Los Angeles
47 publications, 1.54%
|
|
University of Illinois Urbana-Champaign
45 publications, 1.48%
|
|
University College London
44 publications, 1.45%
|
|
Columbia University
42 publications, 1.38%
|
|
Boston University
41 publications, 1.35%
|
|
ETH Zurich
40 publications, 1.31%
|
|
University of Texas at Austin
33 publications, 1.08%
|
|
Technical University of Berlin
32 publications, 1.05%
|
|
Purdue University
32 publications, 1.05%
|
|
Tsinghua University
31 publications, 1.02%
|
|
Université Catholique de Louvain
30 publications, 0.99%
|
|
Northwestern University
29 publications, 0.95%
|
|
Cornell University
26 publications, 0.85%
|
|
University of Michigan
26 publications, 0.85%
|
|
University of Waterloo
25 publications, 0.82%
|
|
University of California, Riverside
23 publications, 0.76%
|
|
University of Maryland, College Park
22 publications, 0.72%
|
|
University of Pennsylvania
22 publications, 0.72%
|
|
Yale University
21 publications, 0.69%
|
|
Duke University
20 publications, 0.66%
|
|
Lawrence Berkeley National Laboratory
18 publications, 0.59%
|
|
University of Delaware
17 publications, 0.56%
|
|
University of Twente
15 publications, 0.49%
|
|
Korea Advanced Institute of Science and Technology
15 publications, 0.49%
|
|
Polytechnic University of Turin
14 publications, 0.46%
|
|
Sorbonne University
14 publications, 0.46%
|
|
Northeastern University
14 publications, 0.46%
|
|
Queen Mary University of London
13 publications, 0.43%
|
|
University of Pisa
13 publications, 0.43%
|
|
University of Adelaide
13 publications, 0.43%
|
|
University of Arizona
13 publications, 0.43%
|
|
University of Toronto
13 publications, 0.43%
|
|
Technical University of Munich
12 publications, 0.39%
|
|
University of California, Irvine
12 publications, 0.39%
|
|
Free University of Berlin
11 publications, 0.36%
|
|
Harvard University
11 publications, 0.36%
|
|
University of California, Santa Barbara
11 publications, 0.36%
|
|
Max Planck Institute for Software Systems
11 publications, 0.36%
|
|
University of Minnesota
11 publications, 0.36%
|
|
Lahore University of Management Sciences
10 publications, 0.33%
|
|
École Polytechnique Fédérale de Lausanne
10 publications, 0.33%
|
|
North Carolina State University
10 publications, 0.33%
|
|
Indian Institute of Technology Bombay
9 publications, 0.3%
|
|
KTH Royal Institute of Technology
9 publications, 0.3%
|
|
William Marsh Rice University
9 publications, 0.3%
|
|
Case Western Reserve University
9 publications, 0.3%
|
|
University of California, Santa Cruz
9 publications, 0.3%
|
|
Budapest University of Technology and Economics
9 publications, 0.3%
|
|
Lancaster University
9 publications, 0.3%
|
|
RWTH Aachen University
9 publications, 0.3%
|
|
Technical University of Darmstadt
9 publications, 0.3%
|
|
Hamburg University of Applied Sciences
9 publications, 0.3%
|
|
University of North Carolina at Chapel Hill
9 publications, 0.3%
|
|
Tel Aviv University
8 publications, 0.26%
|
|
Technion – Israel Institute of Technology
8 publications, 0.26%
|
|
University of Helsinki
8 publications, 0.26%
|
|
Aalto University
8 publications, 0.26%
|
|
Polytechnic University of Milan
8 publications, 0.26%
|
|
National Taiwan University
8 publications, 0.26%
|
|
Stony Brook University
8 publications, 0.26%
|
|
Hebrew University of Jerusalem
7 publications, 0.23%
|
|
Delft University of Technology
7 publications, 0.23%
|
|
University of Oslo
7 publications, 0.23%
|
|
California Institute of Technology
7 publications, 0.23%
|
|
University of Waikato
7 publications, 0.23%
|
|
Swinburne University of Technology
7 publications, 0.23%
|
|
National University of Defense Technology
7 publications, 0.23%
|
|
University of Vienna
7 publications, 0.23%
|
|
University of Kentucky
7 publications, 0.23%
|
|
Texas A&M University
7 publications, 0.23%
|
|
University of Liège
6 publications, 0.2%
|
|
Aalborg University
6 publications, 0.2%
|
|
University of Oxford
6 publications, 0.2%
|
|
University of Brescia
6 publications, 0.2%
|
|
University of Auckland
6 publications, 0.2%
|
|
University of Melbourne
6 publications, 0.2%
|
|
Rutgers, The State University of New Jersey
6 publications, 0.2%
|
|
Ohio State University
6 publications, 0.2%
|
|
Rensselaer Polytechnic Institute
6 publications, 0.2%
|
|
University of Göttingen
6 publications, 0.2%
|
|
Universidad Carlos III de Madrid
6 publications, 0.2%
|
|
University of Ottawa
6 publications, 0.2%
|
|
University of Colorado Boulder
6 publications, 0.2%
|
|
Karlsruhe Institute of Technology
5 publications, 0.16%
|
|
Ghent University
5 publications, 0.16%
|
|
University of Strasbourg
5 publications, 0.16%
|
|
Imperial College London
5 publications, 0.16%
|
|
National University of Singapore
5 publications, 0.16%
|
|
Michigan State University
5 publications, 0.16%
|
|
Show all (70 more) | |
20
40
60
80
100
120
|
Publishing organizations in 5 years
1
2
3
4
5
6
7
8
|
|
Princeton University
8 publications, 6.4%
|
|
Columbia University
7 publications, 5.6%
|
|
University of Twente
6 publications, 4.8%
|
|
Queen Mary University of London
5 publications, 4%
|
|
University of California, San Diego
5 publications, 4%
|
|
Université Catholique de Louvain
4 publications, 3.2%
|
|
Stanford University
4 publications, 3.2%
|
|
University of California, Berkeley
4 publications, 3.2%
|
|
University of Washington
4 publications, 3.2%
|
|
Technical University of Munich
3 publications, 2.4%
|
|
ETH Zurich
3 publications, 2.4%
|
|
Polytechnic University of Turin
3 publications, 2.4%
|
|
University of Oxford
3 publications, 2.4%
|
|
University of Cambridge
3 publications, 2.4%
|
|
Cornell University
3 publications, 2.4%
|
|
University of Illinois Urbana-Champaign
3 publications, 2.4%
|
|
Brandenburg University of Technology Cottbus–Senftenberg
3 publications, 2.4%
|
|
Lahore University of Management Sciences
2 publications, 1.6%
|
|
University of Strasbourg
2 publications, 1.6%
|
|
KTH Royal Institute of Technology
2 publications, 1.6%
|
|
Delft University of Technology
2 publications, 1.6%
|
|
Polytechnic University of Milan
2 publications, 1.6%
|
|
University of Oslo
2 publications, 1.6%
|
|
University of Sydney
2 publications, 1.6%
|
|
University of Pisa
2 publications, 1.6%
|
|
Georgia Institute of technology
2 publications, 1.6%
|
|
University of Auckland
2 publications, 1.6%
|
|
Technical University of Berlin
2 publications, 1.6%
|
|
Eötvös Loránd University (University of Budapest)
2 publications, 1.6%
|
|
Helmholtz Center for Information Security
2 publications, 1.6%
|
|
University of Vienna
2 publications, 1.6%
|
|
King Abdullah University of Science and Technology
1 publication, 0.8%
|
|
New York University Abu Dhabi
1 publication, 0.8%
|
|
National University of Sciences & Technology
1 publication, 0.8%
|
|
Indian Institute of Technology Bombay
1 publication, 0.8%
|
|
University of Tübingen
1 publication, 0.8%
|
|
Technion – Israel Institute of Technology
1 publication, 0.8%
|
|
Hebrew University of Jerusalem
1 publication, 0.8%
|
|
Ariel University
1 publication, 0.8%
|
|
University of Helsinki
1 publication, 0.8%
|
|
Karlstad University
1 publication, 0.8%
|
|
Università della Svizzera italiana
1 publication, 0.8%
|
|
University of Oulu
1 publication, 0.8%
|
|
University of Turin
1 publication, 0.8%
|
|
Imperial College London
1 publication, 0.8%
|
|
University College London
1 publication, 0.8%
|
|
Sorbonne University
1 publication, 0.8%
|
|
University of Southern California
1 publication, 0.8%
|
|
Stony Brook University
1 publication, 0.8%
|
|
Yale University
1 publication, 0.8%
|
|
University of Eastern Piedmont Amadeo Avogadro
1 publication, 0.8%
|
|
University of Waikato
1 publication, 0.8%
|
|
Northwestern University
1 publication, 0.8%
|
|
Rutgers, The State University of New Jersey
1 publication, 0.8%
|
|
Case Western Reserve University
1 publication, 0.8%
|
|
Duke University
1 publication, 0.8%
|
|
University of California, Los Angeles
1 publication, 0.8%
|
|
University of California, Santa Barbara
1 publication, 0.8%
|
|
Vienna University of Technology
1 publication, 0.8%
|
|
University of Texas at Austin
1 publication, 0.8%
|
|
University of Thessaly
1 publication, 0.8%
|
|
Trinity College Dublin
1 publication, 0.8%
|
|
Max Planck Institute for Software Systems
1 publication, 0.8%
|
|
University of Buenos Aires
1 publication, 0.8%
|
|
Ludwig Maximilian University of Munich
1 publication, 0.8%
|
|
University of St Andrews
1 publication, 0.8%
|
|
University of Michigan
1 publication, 0.8%
|
|
Lancaster University
1 publication, 0.8%
|
|
University of Waterloo
1 publication, 0.8%
|
|
Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute
1 publication, 0.8%
|
|
RWTH Aachen University
1 publication, 0.8%
|
|
Technical University of Braunschweig
1 publication, 0.8%
|
|
Technical University of Darmstadt
1 publication, 0.8%
|
|
University of Minnesota
1 publication, 0.8%
|
|
Saarland University
1 publication, 0.8%
|
|
University of Mannheim
1 publication, 0.8%
|
|
Purdue University
1 publication, 0.8%
|
|
Ilmenau University of Technology
1 publication, 0.8%
|
|
Brown University
1 publication, 0.8%
|
|
Federal University of Rio Grande
1 publication, 0.8%
|
|
University of Salzburg
1 publication, 0.8%
|
|
University of Wisconsin–Madison
1 publication, 0.8%
|
|
University of Porto
1 publication, 0.8%
|
|
AGH University of Krakow
1 publication, 0.8%
|
|
Universidad Carlos III de Madrid
1 publication, 0.8%
|
|
Polytechnic University of Catalonia
1 publication, 0.8%
|
|
Université Côte d'Azur
1 publication, 0.8%
|
|
University College Dublin
1 publication, 0.8%
|
|
Show all (58 more) | |
1
2
3
4
5
6
7
8
|
Publishing countries
200
400
600
800
1000
1200
1400
1600
1800
|
|
USA
|
USA, 1622, 53.29%
USA
1622 publications, 53.29%
|
United Kingdom
|
United Kingdom, 206, 6.77%
United Kingdom
206 publications, 6.77%
|
Germany
|
Germany, 164, 5.39%
Germany
164 publications, 5.39%
|
China
|
China, 109, 3.58%
China
109 publications, 3.58%
|
France
|
France, 101, 3.32%
France
101 publications, 3.32%
|
Canada
|
Canada, 87, 2.86%
Canada
87 publications, 2.86%
|
Switzerland
|
Switzerland, 79, 2.6%
Switzerland
79 publications, 2.6%
|
Italy
|
Italy, 75, 2.46%
Italy
75 publications, 2.46%
|
Australia
|
Australia, 52, 1.71%
Australia
52 publications, 1.71%
|
Belgium
|
Belgium, 48, 1.58%
Belgium
48 publications, 1.58%
|
Republic of Korea
|
Republic of Korea, 47, 1.54%
Republic of Korea
47 publications, 1.54%
|
Japan
|
Japan, 47, 1.54%
Japan
47 publications, 1.54%
|
Spain
|
Spain, 39, 1.28%
Spain
39 publications, 1.28%
|
Israel
|
Israel, 34, 1.12%
Israel
34 publications, 1.12%
|
Sweden
|
Sweden, 30, 0.99%
Sweden
30 publications, 0.99%
|
Netherlands
|
Netherlands, 29, 0.95%
Netherlands
29 publications, 0.95%
|
India
|
India, 24, 0.79%
India
24 publications, 0.79%
|
Finland
|
Finland, 23, 0.76%
Finland
23 publications, 0.76%
|
Austria
|
Austria, 17, 0.56%
Austria
17 publications, 0.56%
|
Greece
|
Greece, 17, 0.56%
Greece
17 publications, 0.56%
|
Brazil
|
Brazil, 15, 0.49%
Brazil
15 publications, 0.49%
|
New Zealand
|
New Zealand, 15, 0.49%
New Zealand
15 publications, 0.49%
|
Hungary
|
Hungary, 14, 0.46%
Hungary
14 publications, 0.46%
|
Pakistan
|
Pakistan, 14, 0.46%
Pakistan
14 publications, 0.46%
|
Singapore
|
Singapore, 12, 0.39%
Singapore
12 publications, 0.39%
|
Norway
|
Norway, 10, 0.33%
Norway
10 publications, 0.33%
|
Denmark
|
Denmark, 9, 0.3%
Denmark
9 publications, 0.3%
|
Portugal
|
Portugal, 8, 0.26%
Portugal
8 publications, 0.26%
|
Ireland
|
Ireland, 8, 0.26%
Ireland
8 publications, 0.26%
|
Iraq
|
Iraq, 7, 0.23%
Iraq
7 publications, 0.23%
|
Romania
|
Romania, 4, 0.13%
Romania
4 publications, 0.13%
|
Saudi Arabia
|
Saudi Arabia, 4, 0.13%
Saudi Arabia
4 publications, 0.13%
|
Philippines
|
Philippines, 4, 0.13%
Philippines
4 publications, 0.13%
|
UAE
|
UAE, 3, 0.1%
UAE
3 publications, 0.1%
|
Russia
|
Russia, 2, 0.07%
Russia
2 publications, 0.07%
|
Venezuela
|
Venezuela, 2, 0.07%
Venezuela
2 publications, 0.07%
|
Qatar
|
Qatar, 2, 0.07%
Qatar
2 publications, 0.07%
|
Luxembourg
|
Luxembourg, 2, 0.07%
Luxembourg
2 publications, 0.07%
|
Mexico
|
Mexico, 2, 0.07%
Mexico
2 publications, 0.07%
|
Poland
|
Poland, 2, 0.07%
Poland
2 publications, 0.07%
|
Slovenia
|
Slovenia, 2, 0.07%
Slovenia
2 publications, 0.07%
|
Thailand
|
Thailand, 2, 0.07%
Thailand
2 publications, 0.07%
|
Estonia
|
Estonia, 1, 0.03%
Estonia
1 publication, 0.03%
|
Argentina
|
Argentina, 1, 0.03%
Argentina
1 publication, 0.03%
|
Iceland
|
Iceland, 1, 0.03%
Iceland
1 publication, 0.03%
|
Kuwait
|
Kuwait, 1, 0.03%
Kuwait
1 publication, 0.03%
|
Lebanon
|
Lebanon, 1, 0.03%
Lebanon
1 publication, 0.03%
|
Paraguay
|
Paraguay, 1, 0.03%
Paraguay
1 publication, 0.03%
|
Senegal
|
Senegal, 1, 0.03%
Senegal
1 publication, 0.03%
|
Croatia
|
Croatia, 1, 0.03%
Croatia
1 publication, 0.03%
|
Czech Republic
|
Czech Republic, 1, 0.03%
Czech Republic
1 publication, 0.03%
|
Chile
|
Chile, 1, 0.03%
Chile
1 publication, 0.03%
|
Eswatini
|
Eswatini, 1, 0.03%
Eswatini
1 publication, 0.03%
|
Show all (23 more) | |
200
400
600
800
1000
1200
1400
1600
1800
|
Publishing countries in 5 years
5
10
15
20
25
30
35
40
45
50
|
|
USA
|
USA, 49, 39.2%
USA
49 publications, 39.2%
|
United Kingdom
|
United Kingdom, 13, 10.4%
United Kingdom
13 publications, 10.4%
|
Germany
|
Germany, 10, 8%
Germany
10 publications, 8%
|
Italy
|
Italy, 9, 7.2%
Italy
9 publications, 7.2%
|
Netherlands
|
Netherlands, 8, 6.4%
Netherlands
8 publications, 6.4%
|
France
|
France, 7, 5.6%
France
7 publications, 5.6%
|
Belgium
|
Belgium, 4, 3.2%
Belgium
4 publications, 3.2%
|
Spain
|
Spain, 4, 3.2%
Spain
4 publications, 3.2%
|
Switzerland
|
Switzerland, 4, 3.2%
Switzerland
4 publications, 3.2%
|
Austria
|
Austria, 3, 2.4%
Austria
3 publications, 2.4%
|
Israel
|
Israel, 3, 2.4%
Israel
3 publications, 2.4%
|
Iraq
|
Iraq, 3, 2.4%
Iraq
3 publications, 2.4%
|
New Zealand
|
New Zealand, 3, 2.4%
New Zealand
3 publications, 2.4%
|
Sweden
|
Sweden, 3, 2.4%
Sweden
3 publications, 2.4%
|
Australia
|
Australia, 2, 1.6%
Australia
2 publications, 1.6%
|
Hungary
|
Hungary, 2, 1.6%
Hungary
2 publications, 1.6%
|
Norway
|
Norway, 2, 1.6%
Norway
2 publications, 1.6%
|
Pakistan
|
Pakistan, 2, 1.6%
Pakistan
2 publications, 1.6%
|
Finland
|
Finland, 2, 1.6%
Finland
2 publications, 1.6%
|
China
|
China, 1, 0.8%
China
1 publication, 0.8%
|
Portugal
|
Portugal, 1, 0.8%
Portugal
1 publication, 0.8%
|
Argentina
|
Argentina, 1, 0.8%
Argentina
1 publication, 0.8%
|
Brazil
|
Brazil, 1, 0.8%
Brazil
1 publication, 0.8%
|
Greece
|
Greece, 1, 0.8%
Greece
1 publication, 0.8%
|
India
|
India, 1, 0.8%
India
1 publication, 0.8%
|
Ireland
|
Ireland, 1, 0.8%
Ireland
1 publication, 0.8%
|
Canada
|
Canada, 1, 0.8%
Canada
1 publication, 0.8%
|
UAE
|
UAE, 1, 0.8%
UAE
1 publication, 0.8%
|
Poland
|
Poland, 1, 0.8%
Poland
1 publication, 0.8%
|
Saudi Arabia
|
Saudi Arabia, 1, 0.8%
Saudi Arabia
1 publication, 0.8%
|
Philippines
|
Philippines, 1, 0.8%
Philippines
1 publication, 0.8%
|
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